Don’t bother with a StackShare scraper. Get a fresh dataset.
If you're thinking about a StackShare scraper, consider getting a ready-to-use StackShare dataset, instead. Save time and resources with extensive and continuously refreshed data. To scrape StackShare data, your company will need to build and maintain scraping tools, which also often encounter anti-scraping solutions.
What is StackShare data?
| Data Points | Example Values |
|---|---|
| Title | Machine Learning Engineer |
| Location | San Francisco, CA, US |
| Remote | true |
| Tools | Dream-framework, hadoop |
| Company name | |
| Company stack URL | https://stackshare.io/companies/pinterest |
What is StackShare data?
Our StackShare data consists of the following datasets: StackShare Companies, StackShare Tools, and StackShare Jobs. StackShare data is a great technographic data source, containing information about companies’ tech stacks. This data can be used to make tech stack-related decisions for market research, investment, or lead generation.
Download the full sample to check our data structure and dictionary.
Why are datasets better than scrapers?
| Features | StackShare datasets | StackShare scrapers |
|---|---|---|
| Simple to use |
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| Stable delivery and formats |
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| Cost-effective* |
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| Historic changes |
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| Data collection and expertise required |
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| Real-time data |
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*if going for large volumes of data
